Next Generation Sequencing (NGS) for quantitative transcriptomic analysis of colorectal tumor cell lines and their ENU mutants

Purpose: To understand differences of gene expression profiles between colorectal cell lines and their ENU mutants. Methods: RNA profiles were generated by deep sequencing using Illumina Next-seq. Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (GRCm38 release-95). Conclusions: Our study represents the detailed differential transcriptomic analysis using ENU mutants of colorectal tumors, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. Overall design: mRNA profiles of tumors were generated by deep sequencing, in triplicate, using Illumina Next-seq.